Epitope Prediction

Epitope prediction focuses on computationally identifying the specific regions of an antigen that bind to antibodies, crucial for vaccine and therapeutic antibody design. Current research heavily utilizes deep learning, employing architectures like graph neural networks and transformers, often incorporating multi-modal data (sequence and structure) and pre-trained models to improve prediction accuracy and handle the inherent variability of antibody-antigen interactions. These advancements are significantly impacting the efficiency and effectiveness of antibody engineering and vaccine development by reducing reliance on expensive and time-consuming experimental methods. The development of large, curated datasets is also a key focus, enabling more robust benchmarking and algorithm development.